Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method implemented by one or more computers, the method comprising: obtaining a plurality of search results for a query based on first relevance scores; classifying the plurality of search results into a plurality of classifications; generating second relevance scores for the plurality of search results based on respective rankings of the plurality of search results in corresponding classifications of the plurality of classifications; and ranking the plurality of search results based on the first relevance scores and the second relevance scores.
This invention relates to improving search result ranking by incorporating classification-based relevance scoring. The problem addressed is that traditional search engines rely solely on initial relevance scores, which may not fully capture the nuanced relationships between search results. The solution involves a multi-step process to enhance ranking accuracy. First, a set of search results is obtained for a given query, each result initially scored by a first relevance metric. These results are then classified into distinct categories or groups. Within each classification, the results are re-ranked based on their relative positions, generating second relevance scores that reflect their prominence within their respective groups. Finally, the search results are re-ranked by combining the original first relevance scores with these new second relevance scores, producing a more refined and contextually aware ranking. This approach leverages both broad relevance and intra-class ranking to improve search result quality. The method is implemented by one or more computers, ensuring scalability and efficiency in processing large datasets. The invention is particularly useful in domains where search results span diverse topics or categories, such as e-commerce, academic research, or general web search.
2. The method of claim 1 , further comprising extracting a preset number of search results from the plurality of search results.
A system and method for processing search results involves retrieving a plurality of search results from a search engine in response to a user query. The method includes analyzing the search results to identify relevant information, such as metadata, content, or other attributes, and then extracting a preset number of search results from the plurality of search results. The extracted results are selected based on predefined criteria, such as relevance, ranking, or user preferences, to provide a refined subset of the original search results. This approach improves search efficiency by reducing the volume of results while maintaining high-quality, relevant information. The method may also involve further processing the extracted results, such as filtering, ranking, or displaying them in a user interface. The system ensures that the extracted results are optimized for the user's needs, enhancing the overall search experience by delivering more focused and relevant content.
3. The method of claim 2 , wherein the preset number of search results comprises at least one search result from each classification of the plurality of classifications.
This invention relates to search systems that categorize and present search results. The problem addressed is ensuring diverse search results by including at least one result from each predefined classification category, preventing bias toward dominant categories. The method involves classifying search results into multiple categories and selecting a preset number of results that guarantees representation from each category. This ensures balanced visibility across all classifications, improving user experience by avoiding skewed or incomplete results. The system may use predefined rules or algorithms to determine the number of results per category, ensuring fairness in result distribution. The method is particularly useful in applications where diverse perspectives or categories are critical, such as legal, medical, or academic searches. By enforcing inclusion of at least one result from each classification, the system mitigates the risk of overlooking relevant but less dominant categories. The approach can be applied to any search system where categorized results are presented, enhancing fairness and comprehensiveness in information retrieval.
4. The method of claim 2 , wherein the query is received from a client, and the method further comprises providing the preset number of search results to the client for display.
A system and method for processing search queries involves receiving a query from a client device and generating a set of search results. The method includes filtering the search results based on predefined criteria to select a subset of results, where the filtering may involve ranking, relevance scoring, or other selection techniques. The filtered subset is then provided to the client for display, ensuring that only a preset number of results are returned. This approach optimizes search performance by reducing the computational load and improving response times while maintaining result quality. The system may further include preprocessing steps to refine the query or results before filtering, ensuring efficiency and accuracy. The method is particularly useful in large-scale search applications where minimizing latency and resource usage is critical.
5. The method of claim 2 , further comprising storing the query, the preset number of search results, and a corresponding relationship between the query and the preset number of search results into a database.
This invention relates to search result management systems, specifically addressing the challenge of efficiently storing and retrieving search queries along with their corresponding results. The system captures a user's search query and retrieves a preset number of search results based on the query. The key innovation involves storing the query, the preset number of search results, and the relationship between them in a database. This allows for tracking and analysis of search patterns, enabling personalized recommendations or performance optimization. The database stores the query, the number of results returned, and their association, ensuring that historical search data is preserved for future reference. This stored data can be used to refine search algorithms, improve user experience, or analyze trends in search behavior. The system ensures that search queries and their results are systematically recorded, facilitating data-driven improvements in search functionality. By maintaining this structured relationship, the system enhances search efficiency and adaptability over time.
6. The method of claim 2 , wherein the preset number is determined based on a number of the plurality of classification.
This invention relates to a method for optimizing classification processes in data analysis or machine learning systems. The problem addressed is the need to dynamically adjust system parameters based on the number of classifications being performed, improving efficiency and accuracy. The method involves determining a preset number, which is used to control an aspect of the classification process. This preset number is calculated based on the total number of classifications being performed. The method ensures that the system adapts to varying workloads by dynamically adjusting this preset number, which could relate to batch sizes, iteration counts, or other performance-related parameters. The underlying process involves a classification system that categorizes data into multiple classes. The preset number, derived from the total classifications, is used to optimize the system's operation. For example, if the number of classifications increases, the preset number may be adjusted to improve throughput or reduce computational overhead. This dynamic adjustment helps maintain performance consistency regardless of the workload size. The invention is particularly useful in scenarios where classification tasks vary in complexity or volume, such as in real-time data processing, large-scale machine learning, or adaptive analytics systems. By linking the preset number to the classification count, the method ensures that the system remains efficient and scalable.
7. The method of claim 1 , wherein the plurality of classifications comprise a plurality of attribute categories or a plurality of geographical locations.
A system and method for classifying data involves categorizing items into multiple classifications, where these classifications can include attribute categories or geographical locations. The method begins by receiving input data, which may be structured or unstructured, and processing it to extract relevant features. These features are then analyzed to determine their relevance to predefined classification criteria. The system applies machine learning or rule-based algorithms to assign the data to one or more classifications based on the extracted features. The classifications can represent different attribute categories, such as product types, user preferences, or other descriptive labels, or they can represent geographical locations, such as regions, cities, or coordinates. The method may also include refining the classifications over time by updating the classification criteria based on new data or user feedback. This approach improves data organization and retrieval by enabling flexible and dynamic categorization of information.
8. One or more storage devices storing executable instructions that, when executed by one or more computers, instruct the one or more computers to perform acts comprising: obtaining a plurality of search results for a query based on first relevance scores; classifying the plurality of search results into a plurality of classifications; generating second relevance scores for the plurality of search results based on respective rankings of the plurality of search results in corresponding classifications of the plurality of classifications; and ranking the plurality of search results based on the first relevance scores and the second relevance scores.
This invention relates to improving search result ranking by incorporating classification-based relevance scoring. The problem addressed is that traditional search engines rely solely on initial relevance scores, which may not fully capture the nuanced relationships between search results. The solution involves a multi-step process to enhance ranking accuracy. First, a search engine retrieves initial search results for a query, each assigned a first relevance score based on conventional ranking algorithms. These results are then classified into multiple categories or classifications, such as topics, themes, or other groupings. Next, the system generates second relevance scores by evaluating the rankings of each result within its respective classification. For example, a result highly ranked within its classification may receive a higher second relevance score. Finally, the system combines the first and second relevance scores to produce a refined ranking of the search results. This approach ensures that results are not only relevant to the query but also well-positioned within their specific classifications, leading to more accurate and contextually appropriate search results. The method improves search quality by leveraging both global and classification-specific relevance metrics.
9. The one or more storage devices of claim 8 , the acts further comprising extracting a preset number of search results from the plurality of search results.
This invention relates to data storage and retrieval systems, specifically improving the efficiency of search result processing. The problem addressed is the computational overhead and resource consumption when handling large volumes of search results, which can slow down system performance and increase latency. The solution involves a method for optimizing search result management by selectively extracting a subset of search results from a larger set of retrieved data. The system first performs a search query across one or more storage devices, generating a plurality of search results. To reduce processing load, the system then extracts a preset number of search results from this larger set. This subset extraction is based on predefined criteria, such as relevance scores, timestamps, or other ranking metrics, ensuring that only the most pertinent or prioritized results are further processed. The extracted subset is then used for subsequent operations, such as display, analysis, or further filtering, while the remaining results are either discarded or stored for potential future use. This approach minimizes resource usage by avoiding unnecessary processing of low-priority or redundant data, thereby improving system efficiency and response times. The method is particularly useful in large-scale data environments where search operations generate extensive result sets, such as databases, cloud storage systems, or enterprise search applications.
10. The one or more storage devices of claim 9 , wherein the preset number of search results comprises at least one search result from each classification of the plurality of classifications.
A system for organizing and retrieving search results involves storing data in one or more storage devices, where the data is classified into multiple categories. When a search query is processed, the system generates a set of search results that includes at least one result from each of the predefined classifications. This ensures that the search results cover a broad range of categories, preventing bias toward a single classification. The system dynamically adjusts the number of results returned from each classification based on relevance or other criteria, while maintaining the requirement that at least one result from each classification is included. This approach improves search result diversity, particularly in applications where comprehensive coverage of different categories is important, such as in legal, medical, or technical databases where missing a relevant classification could lead to incomplete or misleading results. The system may also prioritize results within each classification based on factors like relevance, recency, or user preferences, while still ensuring that no classification is excluded from the final output.
11. The one or more storage devices of claim 9 , wherein the query is received from a client, and the method further comprises providing the preset number of search results to the client for display.
This invention relates to a system for processing and displaying search results from a database. The system addresses the challenge of efficiently retrieving and presenting a controlled number of search results to a user, ensuring optimal performance and user experience. The system includes one or more storage devices storing a database and a processor configured to execute a search query on the database. The processor retrieves a preset number of search results from the database based on the query. The query is received from a client device, and the system provides the preset number of search results to the client for display. The system may also include a network interface for communication between the client and the server, and a user interface for configuring the preset number of search results. The invention ensures that the search results are delivered efficiently and in a user-friendly manner, improving the overall search experience. The system may also include additional features such as filtering, sorting, and ranking of search results to enhance relevance and usability.
12. The one or more storage devices of claim 9 , further comprising storing the query, the preset number of search results, and a corresponding relationship between the query and the preset number of search results into a database.
This invention relates to a system for managing search queries and results in a database. The system addresses the problem of efficiently storing and retrieving search queries along with their corresponding results to improve search performance and user experience. The system includes one or more storage devices configured to store a query, a preset number of search results associated with that query, and a corresponding relationship between the query and the preset number of search results. This stored relationship allows for quick retrieval of previously generated search results when the same query is submitted again, reducing the need for repeated processing. The system may also include a search engine that processes the query to generate the search results and a database that stores the query, the preset number of search results, and the relationship between them. The stored data can be used to optimize future searches by leveraging cached results, improving response times, and reducing computational overhead. The system ensures that the stored search results are associated with the correct query, maintaining accuracy and relevance in subsequent searches. This approach enhances efficiency in search operations, particularly in environments where the same queries are frequently repeated.
13. The one or more storage devices of claim 9 , wherein the preset number is determined based on a number of the plurality of classification.
This invention relates to data storage systems and addresses the challenge of efficiently managing and classifying stored data. The system includes one or more storage devices configured to store a plurality of data items, each associated with one or more classifications. The storage devices are further configured to determine a preset number of classifications for organizing the data items. This preset number is dynamically calculated based on the total number of classifications available in the system. The system ensures that data items are distributed across the classifications in a balanced manner, optimizing storage efficiency and retrieval performance. The classification process involves analyzing the data items and assigning them to the appropriate categories, with the preset number serving as a threshold to prevent over-classification or under-classification. This approach enhances data organization, reduces redundancy, and improves searchability within the storage system. The invention is particularly useful in large-scale data management environments where maintaining an organized and scalable classification structure is critical. By dynamically adjusting the preset number based on the number of classifications, the system adapts to varying data volumes and ensures consistent performance.
14. The one or more storage devices of claim 8 , wherein the plurality of classifications comprise a plurality of attribute categories or a plurality of geographical locations.
15. A system comprising: one or more processors; storage media storing executable instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: obtaining a plurality of search results for a query based on first relevance scores; classifying the plurality of search results into a plurality of classifications; generating second relevance scores for the plurality of search results based on respective rankings of the plurality of search results in corresponding classifications of the plurality of classifications; and ranking the plurality of search results based on the first relevance scores and the second relevance scores.
The system improves search result ranking by refining initial relevance scores through classification-based re-ranking. In search engines, determining the most relevant results for a query is challenging due to the diversity of content and user intent. Traditional relevance scoring may not fully capture contextual or categorical distinctions among results. This system addresses the problem by first obtaining search results with initial relevance scores. The results are then classified into multiple categories or classifications, such as topics, content types, or other groupings. Each result is re-scored based on its rank within its respective classification, generating a second set of relevance scores. The final ranking combines the original and re-scored relevance scores to produce a more nuanced and accurate ordering of results. This approach enhances search quality by leveraging both broad relevance and contextual ranking within specific classifications. The system is implemented using one or more processors executing instructions stored in memory, ensuring efficient computation and real-time applicability.
16. The system of claim 15 , the acts further comprising extracting a preset number of search results from the plurality of search results.
This invention relates to a system for processing and refining search results to improve relevance and usability. The system addresses the problem of overwhelming users with excessive or low-quality search results, which can reduce efficiency and user satisfaction. The system includes a search engine that generates a plurality of search results in response to a user query. These results are then processed to extract a preset number of the most relevant or high-quality results, ensuring the user receives a concise and manageable set of options. The system may also include additional features such as filtering, ranking, or clustering of results to further enhance relevance. The preset number of extracted results can be dynamically adjusted based on user preferences, query complexity, or other contextual factors. This approach optimizes the search experience by reducing information overload while maintaining the most valuable results. The system may be applied in various domains, including web search, enterprise search, or specialized databases, to improve search efficiency and user engagement.
17. The system of claim 16 , wherein the preset number of search results comprises at least one search result from each classification of the plurality of classifications.
A system for organizing and presenting search results is disclosed, addressing the challenge of efficiently categorizing and displaying diverse information to users. The system classifies search results into multiple predefined categories, ensuring that each category is represented in the final output. When a user performs a search, the system retrieves results and distributes them across these classifications. The system then selects a preset number of results, ensuring that at least one result from each classification is included. This approach prevents dominance by a single category and promotes balanced representation of different types of information. The classifications may be based on relevance, content type, source, or other criteria. The system dynamically adjusts the selection process to maintain diversity, even if some classifications have fewer results than others. This method enhances user experience by providing a well-rounded set of search results, avoiding bias toward any particular category. The system may also prioritize results within each classification based on relevance or other ranking factors. The overall goal is to deliver a comprehensive and varied set of search results that cover multiple perspectives or types of content.
18. The system of claim 16 , wherein the query is received from a client, and the method further comprises providing the preset number of search results to the client for display.
A system and method for processing search queries involves receiving a query from a client device and generating a set of search results. The system filters these results to select a preset number of the most relevant results based on predefined criteria, such as relevance scores or user preferences. The filtered results are then provided to the client for display. The system may also include a search engine that processes the query, a ranking module that assigns relevance scores to the results, and a filtering module that enforces the preset number of results. The method ensures that only the most relevant results are presented to the user, improving search efficiency and user experience. The system may be integrated into web search platforms, enterprise search tools, or other applications requiring filtered search results. The preset number of results can be dynamically adjusted based on user behavior or system performance. The system may also include additional features such as caching frequently accessed results or personalizing results based on user history. The overall goal is to optimize search performance by reducing the volume of results while maintaining high relevance.
19. The system of claim 16 , further comprising storing the query, the preset number of search results, and a corresponding relationship between the query and the preset number of search results into a database.
A system for managing search queries and results is disclosed, addressing the challenge of efficiently tracking and retrieving search data. The system includes a search interface that receives a query from a user and retrieves a preset number of search results based on the query. The system further stores the query, the preset number of search results, and the corresponding relationship between the query and the preset number of search results in a database. This allows for the tracking of search patterns, optimization of search algorithms, and retrieval of historical search data. The system may also include a user interface for displaying the search results and a processing unit for executing the search operations. The database stores the query data to enable analysis of search trends and improve future search performance. The system ensures that search queries and their corresponding results are systematically recorded, facilitating data-driven improvements in search functionality.
20. The system of claim 15 , wherein the plurality of classifications comprise a plurality of attribute categories or a plurality of geographical locations.
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January 16, 2018
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